EvoPhylo: an R package for pre- and postprocessing of morphological data from relaxed clock Bayesian phylogenetics

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1111/2041-210X.14128. This is version 2 of this Preprint.

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Authors

Tiago R. Simões, Noah Greifer, Joëlle Barido-Sottani, Stephanie E. Pierce

Abstract

1. Relaxed clock Bayesian evolutionary inference (BEI) enables the co-estimation of phylogenetic trees and evolutionary parameters associated with models of character and lineage evolution. Fast advances in new model developments over the past decade have boosted BEI as a major macroevolutionary analytical framework using morphological and/or molecular data across vastly different study systems. However, there is a limited availability of bioinformatic tools to pre- and post-process data from BEI, such as identifying morphological data partitions, or statistically testing and creating publication quality plots of evolutionary hypotheses using the output from BEI.
2. Here we introduce EvoPhylo, an R package to perform automated morphological character partitioning for phylogenetic analyses and analyze macroevolutionary parameter outputs from relaxed clock (time-calibrated) BEI.
3. We present the theoretical background behind EvoPhylo’s functions and analytical tools for evolutionary hypothesis testing, its potential uses, and interpretation of its results with a series of vignettes and links to a step-by-step tutorial.
4. EvoPhylo will facilitate utilization of Bayesian relaxed clocks as a tool for macroevolutionary inference across a wide range of users and fields of research, especially those that use morphological datasets.

DOI

https://doi.org/10.32942/osf.io/3mkf9

Subjects

Bioinformatics, Ecology and Evolutionary Biology, Evolution, Life Sciences

Keywords

Bayesian phylogenetics, character partitioning, diversification rates, evolutionary rates, morphology, R., selection

Dates

Published: 2022-06-07 02:27

Last Updated: 2022-06-07 03:01

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License

CC-By Attribution-NonCommercial-NoDerivatives 4.0 International